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Record W2769719269 · doi:10.1002/mabi.201700304

3D Printed Anchoring Sutures for Permanent Shaping of Tissues

2017· article· en· W2769719269 on OpenAlexaff
Wei Wei, Yuxiao Li, Huazhe Yang, Reza Nassab, Fatemeh Shahriyari, Ali Akpek, Xiaofei Guan, Yanhui Liu, Shahrouz Taranejoo, Ali Tamayol, Yu Shrike Zhang, Ali Khademhosseini, Hae Lin Jang

Bibliographic record

VenueMacromolecular Bioscience · 2017
Typearticle
Languageen
FieldMedicine
TopicSurgical Sutures and Adhesives
Canadian institutionsWiLAN (Canada)
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institutes of Health
KeywordsAnchoringSlippingFibrous jointTendon3d printedMaterials scienceBiomedical engineeringMechanical strengthAnatomyStructural engineeringComposite materialEngineeringMedicine

Abstract

fetched live from OpenAlex

Sutures are one of the most widely used devices for adhering separated tissues after injury or surgery. However, most sutures require knotting, which can create a risk of inflammation, and can act as mechanically weak points that often result in breakage and slipping. Here, an anchoring suture is presented with a design that facilitates its propagation parallel to the suturing direction, while maximizing its resistive force against the opposite direction of external force to lock its position in tissues. Different microstructures of suture anchors are systematically designed using orthogonal arrays, and selected based on shape factors associated with mechanical strength. 3D printing is used to fabricate different types of hollow microstructured suture anchors, and optimize their structure for the effective shaping of tissues. To define the structural design for fixing tissues, the maximum force required to pull 3D printed anchors in different directions is examined with tissues. The tissue reshaping function of suture anchors is further simulated ex vivo by using swine ear, nose, and skin, and bovine muscle tendon. This study provides advantages for building functional sutures that can be used for permanently reshaping tissues with enhanced mechanical strength, eliminating the need for knotting to improve surgical efficiency.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.342
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2017
Admission routes1
Has abstractyes

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